1) Know Your Own Audience
The foundation of audience intelligence begins with your own first-party information. First-party data is a combination of the personal information that consumers share when interacting with your brand and the clickstream and online behavioural data your digital properties can track — that is, the details collected on your customer’s path to purchase within your own app or websites. A great first step in translating your first-party data into valuable insights is to identify interesting correlations between your audience’s declared demographic information (age, gender, etc.) and observed patterns of online behaviour (path to purchase, cross-device behaviour etc.).
Many brands group their customers into “personas” so that they are digestible from a higher level and can be easily disseminated across the organisation. Personas are developed based on basic customer profile information collected over time, such as website behaviour, loyalty member data, focus groups or customer surveys. Although personas can be a useful starting point, in some cases they can be overly reductive or outdated.
The better you’re able to meaningfully segment your audience, the more likely you are to find powerful correlations between their unique attributes. Often times large brands will use market research and audience insights tools like Hitwise to better understand the complexity of their own audience.
2) Add Third-Party Data
Most marketers use outside, third-party data vendors to help them gain access to data that could not be collected otherwise; this enables them to target new customers outside of their first-party data set. Marketers can also use third-party data to enhance their audience segmentation by expanding and enriching their current information on their customers.
Supplementing 1st Party Data
First-party clickstream data is often limited to purchase data, customer information, online and in-app behaviour, and in some cases the search terms that led users to your site. Third-party data can provide a clearer and richer picture of how shoppers moved across the web before they arrived at your doorstep, the kind of content they consume, or simply a greater depth of demographic data to flesh out their customer profile. The quality of data is also deeply important. Data providers should be willing to disclose their sources, whether their data sets come from declared or observed audiences, and whether or not these audiences have been modeled.
3) Integrate Your Data Streams
For most organisations, layering multiple data streams and targeting their audiences with personalised, dynamic advertisements requires solving quite a few structural challenges. Marketers must ensure that the first- and third-party data sets that inform their campaigns integrate with one another, accurately represent real consumers, can be optimised in real-time, and remain constantly available to inform media buying.
The Challenge of Disparate Data Sets
In order for your audience insights to effectively power your marketing efforts, it’s vital that your data is collected in one centralised database. The software tools you use for audience intelligence, modeling, and campaign optimisation should freely share data with one another.
Solving the Data Disconnect
Building these integrations in-house can be very expensive: not just in terms of upfront development costs, but in maintenance costs as well. The technology and experience required to support ad targeting is advancing constantly, from the media platforms that host the campaigns, to the devices where the ads are served, which means that integrations will need to be updated as well.
The Importance of Real-Time
It’s crucial that your measurement system is not only robust, but that it’s being actively interpreted in real-time (or as close to it as possible) by the people who need it to inform purchasing decisions.
As the amount of data available increases, so do the challenges surrounding effectively converting consumer research into effective campaigns. As these roadblocks become clearer, forward-thinking marketers can begin to envision a path towards more effective, seamless marketing campaigns. Currently, data-driven marketers are charged with segmenting and distilling the most useful data within and without their organisation.